Answer Posted / Umesh Kumar Kushwaha

To build and evaluate a random forest in R, follow these steps: n1. Install and load the randomForest package (if not already installed). n2. Split your data into training and testing sets. n3. Train the model using the `randomForest()` function: `random_forest_model <- randomForest(dependent_variable ~ independent_variables, data = training_data)`. n4. Predict on the test set with `predict()`: `predictions <- predict(random_forest_model, newdata = testing_data)`. n5. Evaluate the performance of the model using appropriate metrics (e.g., accuracy, AUC-ROC).

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